---
tags:
- image-classification
- timm
library_name: timm
license: mit
datasets:
- cifar10
metrics:
- accuracy
model-index:
  - name: resnet18
    results: 
      - task: 
          type: image-classification
        dataset:
          name: cifar10
          type: cifar10
        metrics:
          - name: accuracy
            type: accuracy
            value: 92.73
---
# Model card for resnet18_cifar10

This is a resnet18 model trained on the cifar10 dataset.
To load this model use the `timm` library and run the following code:
```python
import timm
model = timm.create_model("hf_hub:SamAdamDay/resnet18_cifar10", pretrained=True)
```

The model was trained using the following command:
```bash
./distributed_train.sh --dataset torch/cifar10 --data-dir /root/data --dataset-download --model resnet18 --lr-base 0.3
```

## Metrics

The model has a test accuracy of 92.73.

## Model Details
- **Dataset:** cifar10
- **Number of epochs:** 300
- **Batch size:** 128
- **Base LR:** 0.3
- **LR scheduler:** cosine
- **PyTorch version:** 2.3.0+cu121
- **timm version:** 1.0.7